Data Engineer - AI, Agents, & Context - Revenue Cycle Associate

Huron helps its clients drive growth, enhance performance and sustain leadership in the markets they serve. We help healthcare organizations build innovation capabilities and accelerate key growth initiatives, enabling organizations to own the future, instead of being disrupted by it. Together, we empower clients to create sustainable growth, optimize internal processes and deliver better consumer outcomes. Health systems, hospitals and medical clinics are under immense pressure to improve clinical outcomes and reduce the cost of providing patient care. Investing in new partnerships, clinical services and technology is not enough to create meaningful and substantive change. To succeed long-term, healthcare organizations must empower leaders, clinicians, employees, affiliates and communities to build cultures that foster innovation to achieve the best outcomes for patients. Joining the Huron team means you’ll help our clients evolve and adapt to the rapidly changing healthcare environment and optimize existing business operations, improve clinical outcomes, create a more consumer-centric healthcare experience, and drive physician, patient and employee engagement across the enterprise. Join our team as the expert you are now and create your future.

Key Responsibilities

Build and contribute to the AI context platform

Implement end-to-end pipelines: ingestion → parsing/chunking → enrichment → embeddings → vector indexing → retrieval/serving

Build andmaintainpatterns for incremental refresh, backfills, re-embeddings, deduplication, and lineage across unstructured sources

Contribute to retrieval quality improvements (query strategies, hybrid search, metadata filtering) in partnership with AI engineers

Deliver semantic and governed data products

Implement semantic layers (metrics/entities) that power BI and agent reasoning consistently

Apply established data contracts and context contracts for AI inputs (schemas, metadata requirements, freshness, citation expectations)

Ensure datasets and indexes are documented and reusable

Operational excellence

Support reliability and performance across assigned workstreams: monitoring, alerting, runbooks, and incident response

Contribute to cost and latency optimization across Snowflake and vector infrastructure

AI safety and compliance

Apply security-by-design patterns: RBAC/ABAC, PII redaction, retention controls, and audit logging

Follow established guardrails for AI access to enterprise knowledge in coordination with Security/Legal/Compliance

TRAVEL EXPECTATIONS

• Ability to travel as needed up to 4 times per year.

Required Qualifications

Bachelor's Degree in computer science, engineering, or related field of study

3–6 years in data engineering or data platform roles with strong hands-on delivery

Strong SQL and Python (or Scala